Dr. Brandmaier promotes conceptual and methodological innovation within developmental psychology and in interdisciplinary context. Particularly, he develops methods and computational tools to answer methodological challenges of lifespan psychology. His primary research interests are interindividual differences in behavioral and neural development, brain-behavior relations across the lifespan, and the adaption of datamining and machine learning approaches to challenges of psychological research.

Andreas is interested in exploratory methods to better explain interindividual differences in change such as SEM trees and forests combining structural equation modeling and decision trees; finding alternative and optimal study designs when planning empirical longitudinal studies; and modeling the emergence of individuality and its relationship to brain plasticity. Dr. Brandmaier's recent research has been published in Science, Psychological Bulletin, Psychological Methods, Psychology and Aging, Developmental Psychology, Frontiers in Psychology, Neuroscience, and NeuroImage. In 2015, Andreas Brandmaier won the Heinz-Billing-Award for outstanding contributions to Computational Science.

Structural Equation Model Trees and Forests.

Structural equation model (SEM) trees and forests, a combination of SEMs and decision trees, are data-analytic tool for theory-guided exploration of empirical data. They allow for the automatic selection of variables that predict differences across individuals in specific theoretical models, for instance, differences in latent factor profiles or developmental trajectories.

Terminal Decline in Well-Being

Well-being is often relatively stable across adulthood and old age, but typically exhibits
pronounced deteriorations and vast individual differences in the terminal phase of life. What factors, such as physical health and social support are associated with differences in well-being changes?

Emergence of Individuality

Reliability of Neuroimaging Methods

Magnetic resonance imaging has become an indispensable tool for studying associations of structural and functional properties of the brain with behavior in humans. We developed the ICED framework to identify and separate different measurement characteristics (day, session, or scanner in multisite studies) and their effects on reliability. ICED supports researchers in developing more reliable neuroimaging studies.

Collaborators

The following interactive chart shows my recent collaborations. An edge between two nodes in this graph means that the corresponding two authors have jointly published with me in the last couple of years. By the time you are reading this, this is probably outdated but it shows at least a subset of my valued collaborators. Zoom in and out with the mouse wheel. Click and drag the background to move the graph. Click nodes to highlight individual collaborators and their subnetworks: